Assignment help

· Explain how the chosen statistical test applies to this research question.

· Provide the statistical notation and written explanations for the null and alternative hypotheses.

· Explain the types of errors that can occur.

· Methods

· Participants (1 paragraph)

· List how many participants will be selected.

· Identify who will be the participants and their major demographic characteristics (e.g., sex, age, etc.).

· Explain how participants will be selected for the study.

· Procedures (1-2 paragraphs)

· Identify the variables in the study.

· Describe each variable’s scale of measurement (nominal, ordinal, interval, or ratio) and characteristics (i.e., discrete vs. continuous, qualitative vs. categorical, etc.).

· Provide an operational definition for each variable, explaining how the variables will be measured.

· Results (1-2 paragraphs)

· Describe the statistical test that will be conducted. Be sure to include why the test was chosen and why it is appropriate for this study.  Also, describe the role of post-hoc tests in the analysis.

· Identify the information that will be obtained from the results of this test and what will be needed to draw conclusions regarding the hypotheses.

· Discussion (1 paragraph)

· Identify any expected biases, assumptions, or faults with the proposed study and the use of the identified statistical test.

· Explain what conclusions can and cannot be made for this study, and using this statistical test.

· Describe the practical significance or importance of the results.

The paper should be APA formatted as a research proposal, and approximately 3 pages of content. Include a title page, and a reference page that includes any resources utilized.  

This written assignment is based on the work conducted in the “RD – Basic ANOVA Study” group discussion forum.  Based on this initial work, feedback received, and additional research, students should submit a mini research proposal that calls for the use of one-way or repeated measures ANOVA. 

1. Introduction (1-2 paragraphs)

0. Present the research question of interest.

0. Explain how the chosen statistical test applies to this research question.

0. Provide the statistical notation and written explanations for the null and alternative hypotheses.

0. Explain the types of errors that can occur.

Hint: Note in ANOVA one way we are testing the equality of means for different levels of the independent variable. In the case of repeated measures, we collect data on the same participants under repeated conditions and test their means.

Consider the following scenario. “Participants were assigned to the control group (none), or one of the training groups (short or long).  The short training group received 1 hour of training, while the long training group received 1 hour of training every day for one week.  During the training, participants learned various techniques for decreasing their stress levels.  After a week, each participant was given a puzzle to put together in a stressful environment (e.g., loud noises, bright lights, etc.).  The amount of the puzzle completed in the time frame of 5 minutes was measured according to the number of pieces completed (there were 10 pieces to the puzzle).  It was expected that the two training groups would have different scores on the test than the control group.” This is an example of one-way ANOVA where the average number of puzzles for none, short and long training groups is compared. Note the participants are different for the three groups.

In contrast if you are comparing the average scores of the same set of ten students at three different points in time then it is an example of one-way repeated measures ANOVA. Note the participants are the same for the three time periods.

Useful weblinks:

One-way ANOVA: http://www4.uwsp.edu/psych/stat/12/anova-1w.htm#I http://www2.fiu.edu/~howellip/exanova.htm http://people.richland.edu/james/lecture/m170/ch13-1wy.html http://cba.ualr.edu/smartstat/topics/anova/example.pdf http://wise.cgu.edu/downloads/ANOVA.doc http://www.nd.edu/~rwilliam/stats1/x52.pdf  

One-way repeated measures ANOVA:  https://statistics.laerd.com/statistical-guides/repeated-measures-anova-statistical-guide.php http://www.statisticslectures.com/topics/repeatedmeasuresanova/ http://www.youtube.com/watch?v=VPB3xrsFl4o

For the first example above,

Null hypothesis  

H0: µnone = µshort = µlong

There is no difference in the average number of puzzle pieces completed (performance) between those in the none, short, or long training.

Alternative hypothesis  

H1: µnone ≠µshort ≠ µlong

The average number of pieces completed (performance) of those who did receive training is different than those who did not receive training.

For the second example,

Null hypothesis  

H0: µtest1 = µtest2 = µtest3

There is no difference in the average scores for test1, test2, test3

Alternative hypothesis  

H1: µtest1 < µtest3 < µtest3

The average score increases over time, with scores on test3 being the largest. Note the alternative hypothesis reflects the instructor's claim.

Note type I error occurs when a null hypothesis which is true is rejected. On the other hand, if we reject the alternative hypothesis when it is true then type II error occurs. For the first example type I error occurs when there is no difference in the average number of puzzles completed by the three groups but we incorrectly conclude there is a difference. Define type II error accordingly.

1. Methods

1. Participants (1 paragraph)

1. List how many participants will be selected.

1. Identify who will be the participants and their major demographic characteristics (e.g., sex, age, etc.).

1. Explain how participants will be selected for the study.

Hint: Describe how many participants will be selected for your proposed study. Also explain how the participants will be selected for the study - whether random sampling or any other method of selection. Include a discussion on the characteristics of the sample.

1. Procedures (1-2 paragraphs)

0. Identify the variables in the study.

0. Describe each variable’s scale of measurement (nominal, ordinal, interval, or ratio) and characteristics (i.e., discrete vs. continuous, qualitative vs. categorical, predictor vs. criterion, etc.).

0. Provide an operational definition for each variable, explaining how the variables will be measured.

Hint: For the one-way ANOVA example discussed above there are two variables training (with three levels – none, short and long) and performance measured in terms of number of puzzles completed. In this case the independent variable is training which is nominal and the dependent variable is performance which is ratio. In the case of second example for the one-way repeated measures ANOVA, time is the independent variable which is nominal and the test scores at three different time points are the dependent variables which are of ratio type.

Operational definition describes how the researcher will measure the variable and manipulate it. For example, if your variable is hunger then you need to specify the method that you will use to come up with a number for each respondent in your study. Are you going to rely on self-reported numbers (may not be appropriate as each respondent can define hunger in a different way) or define it as no food intake for a period of 10 hours.

Useful weblinks: